Chapter 2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'sklearn.pipline'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-24-57df521517c2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpreprocessing\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mImputer\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpreprocessing\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mOneHotEncoder\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 12\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpipline\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mPipline\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     13\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpreprocessing\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mStandardScaler\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     14\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'sklearn.pipline'"
     ]
    }
   ],
   "source": [
    "import os \n",
    "import tarfile \n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt \n",
    "import numpy as np \n",
    "from six.moves import urllib \n",
    "from sklearn.model_selection import train_test_split \n",
    "from sklearn.model_selection import StratifiedShuffleSplit \n",
    "from pandas.plotting import scatter_matrix \n",
    "from sklearn.preprocessing import Imputer \n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.pipline import Pipline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "downloadRoot = \"https://raw.githubusercontent.com/ageron/handson-ml/master/\" \n",
    "housing_Path = os.path.join(\"datasets\", \"housing\") \n",
    "housing_URL = downloadRoot + \"datasets/housing/housing.tgz\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Definition of the CategoricalEncoder class, copied from PR #9151.\n",
    "# Just run this cell, or copy it to your code, do not try to understand it (yet).\n",
    "\n",
    "from sklearn.base import BaseEstimator, TransformerMixin\n",
    "from sklearn.utils import check_array\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from scipy import sparse\n",
    "\n",
    "class CategoricalEncoder(BaseEstimator, TransformerMixin):\n",
    "    \"\"\"Encode categorical features as a numeric array.\n",
    "    The input to this transformer should be a matrix of integers or strings,\n",
    "    denoting the values taken on by categorical (discrete) features.\n",
    "    The features can be encoded using a one-hot aka one-of-K scheme\n",
    "    (``encoding='onehot'``, the default) or converted to ordinal integers\n",
    "    (``encoding='ordinal'``).\n",
    "    This encoding is needed for feeding categorical data to many scikit-learn\n",
    "    estimators, notably linear models and SVMs with the standard kernels.\n",
    "    Read more in the :ref:`User Guide <preprocessing_categorical_features>`.\n",
    "    Parameters\n",
    "    ----------\n",
    "    encoding : str, 'onehot', 'onehot-dense' or 'ordinal'\n",
    "        The type of encoding to use (default is 'onehot'):\n",
    "        - 'onehot': encode the features using a one-hot aka one-of-K scheme\n",
    "          (or also called 'dummy' encoding). This creates a binary column for\n",
    "          each category and returns a sparse matrix.\n",
    "        - 'onehot-dense': the same as 'onehot' but returns a dense array\n",
    "          instead of a sparse matrix.\n",
    "        - 'ordinal': encode the features as ordinal integers. This results in\n",
    "          a single column of integers (0 to n_categories - 1) per feature.\n",
    "    categories : 'auto' or a list of lists/arrays of values.\n",
    "        Categories (unique values) per feature:\n",
    "        - 'auto' : Determine categories automatically from the training data.\n",
    "        - list : ``categories[i]`` holds the categories expected in the ith\n",
    "          column. The passed categories are sorted before encoding the data\n",
    "          (used categories can be found in the ``categories_`` attribute).\n",
    "    dtype : number type, default np.float64\n",
    "        Desired dtype of output.\n",
    "    handle_unknown : 'error' (default) or 'ignore'\n",
    "        Whether to raise an error or ignore if a unknown categorical feature is\n",
    "        present during transform (default is to raise). When this is parameter\n",
    "        is set to 'ignore' and an unknown category is encountered during\n",
    "        transform, the resulting one-hot encoded columns for this feature\n",
    "        will be all zeros.\n",
    "        Ignoring unknown categories is not supported for\n",
    "        ``encoding='ordinal'``.\n",
    "    Attributes\n",
    "    ----------\n",
    "    categories_ : list of arrays\n",
    "        The categories of each feature determined during fitting. When\n",
    "        categories were specified manually, this holds the sorted categories\n",
    "        (in order corresponding with output of `transform`).\n",
    "    Examples\n",
    "    --------\n",
    "    Given a dataset with three features and two samples, we let the encoder\n",
    "    find the maximum value per feature and transform the data to a binary\n",
    "    one-hot encoding.\n",
    "    >>> from sklearn.preprocessing import CategoricalEncoder\n",
    "    >>> enc = CategoricalEncoder(handle_unknown='ignore')\n",
    "    >>> enc.fit([[0, 0, 3], [1, 1, 0], [0, 2, 1], [1, 0, 2]])\n",
    "    ... # doctest: +ELLIPSIS\n",
    "    CategoricalEncoder(categories='auto', dtype=<... 'numpy.float64'>,\n",
    "              encoding='onehot', handle_unknown='ignore')\n",
    "    >>> enc.transform([[0, 1, 1], [1, 0, 4]]).toarray()\n",
    "    array([[ 1.,  0.,  0.,  1.,  0.,  0.,  1.,  0.,  0.],\n",
    "           [ 0.,  1.,  1.,  0.,  0.,  0.,  0.,  0.,  0.]])\n",
    "    See also\n",
    "    --------\n",
    "    sklearn.preprocessing.OneHotEncoder : performs a one-hot encoding of\n",
    "      integer ordinal features. The ``OneHotEncoder assumes`` that input\n",
    "      features take on values in the range ``[0, max(feature)]`` instead of\n",
    "      using the unique values.\n",
    "    sklearn.feature_extraction.DictVectorizer : performs a one-hot encoding of\n",
    "      dictionary items (also handles string-valued features).\n",
    "    sklearn.feature_extraction.FeatureHasher : performs an approximate one-hot\n",
    "      encoding of dictionary items or strings.\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, encoding='onehot', categories='auto', dtype=np.float64,\n",
    "                 handle_unknown='error'):\n",
    "        self.encoding = encoding\n",
    "        self.categories = categories\n",
    "        self.dtype = dtype\n",
    "        self.handle_unknown = handle_unknown\n",
    "\n",
    "    def fit(self, X, y=None):\n",
    "        \"\"\"Fit the CategoricalEncoder to X.\n",
    "        Parameters\n",
    "        ----------\n",
    "        X : array-like, shape [n_samples, n_feature]\n",
    "            The data to determine the categories of each feature.\n",
    "        Returns\n",
    "        -------\n",
    "        self\n",
    "        \"\"\"\n",
    "\n",
    "        if self.encoding not in ['onehot', 'onehot-dense', 'ordinal']:\n",
    "            template = (\"encoding should be either 'onehot', 'onehot-dense' \"\n",
    "                        \"or 'ordinal', got %s\")\n",
    "            raise ValueError(template % self.handle_unknown)\n",
    "\n",
    "        if self.handle_unknown not in ['error', 'ignore']:\n",
    "            template = (\"handle_unknown should be either 'error' or \"\n",
    "                        \"'ignore', got %s\")\n",
    "            raise ValueError(template % self.handle_unknown)\n",
    "\n",
    "        if self.encoding == 'ordinal' and self.handle_unknown == 'ignore':\n",
    "            raise ValueError(\"handle_unknown='ignore' is not supported for\"\n",
    "                             \" encoding='ordinal'\")\n",
    "\n",
    "        X = check_array(X, dtype=np.object, accept_sparse='csc', copy=True)\n",
    "        n_samples, n_features = X.shape\n",
    "\n",
    "        self._label_encoders_ = [LabelEncoder() for _ in range(n_features)]\n",
    "\n",
    "        for i in range(n_features):\n",
    "            le = self._label_encoders_[i]\n",
    "            Xi = X[:, i]\n",
    "            if self.categories == 'auto':\n",
    "                le.fit(Xi)\n",
    "            else:\n",
    "                valid_mask = np.in1d(Xi, self.categories[i])\n",
    "                if not np.all(valid_mask):\n",
    "                    if self.handle_unknown == 'error':\n",
    "                        diff = np.unique(Xi[~valid_mask])\n",
    "                        msg = (\"Found unknown categories {0} in column {1}\"\n",
    "                               \" during fit\".format(diff, i))\n",
    "                        raise ValueError(msg)\n",
    "                le.classes_ = np.array(np.sort(self.categories[i]))\n",
    "\n",
    "        self.categories_ = [le.classes_ for le in self._label_encoders_]\n",
    "\n",
    "        return self\n",
    "\n",
    "    def transform(self, X):\n",
    "        \"\"\"Transform X using one-hot encoding.\n",
    "        Parameters\n",
    "        ----------\n",
    "        X : array-like, shape [n_samples, n_features]\n",
    "            The data to encode.\n",
    "        Returns\n",
    "        -------\n",
    "        X_out : sparse matrix or a 2-d array\n",
    "            Transformed input.\n",
    "        \"\"\"\n",
    "        X = check_array(X, accept_sparse='csc', dtype=np.object, copy=True)\n",
    "        n_samples, n_features = X.shape\n",
    "        X_int = np.zeros_like(X, dtype=np.int)\n",
    "        X_mask = np.ones_like(X, dtype=np.bool)\n",
    "\n",
    "        for i in range(n_features):\n",
    "            valid_mask = np.in1d(X[:, i], self.categories_[i])\n",
    "\n",
    "            if not np.all(valid_mask):\n",
    "                if self.handle_unknown == 'error':\n",
    "                    diff = np.unique(X[~valid_mask, i])\n",
    "                    msg = (\"Found unknown categories {0} in column {1}\"\n",
    "                           \" during transform\".format(diff, i))\n",
    "                    raise ValueError(msg)\n",
    "                else:\n",
    "                    # Set the problematic rows to an acceptable value and\n",
    "                    # continue `The rows are marked `X_mask` and will be\n",
    "                    # removed later.\n",
    "                    X_mask[:, i] = valid_mask\n",
    "                    X[:, i][~valid_mask] = self.categories_[i][0]\n",
    "            X_int[:, i] = self._label_encoders_[i].transform(X[:, i])\n",
    "\n",
    "        if self.encoding == 'ordinal':\n",
    "            return X_int.astype(self.dtype, copy=False)\n",
    "\n",
    "        mask = X_mask.ravel()\n",
    "        n_values = [cats.shape[0] for cats in self.categories_]\n",
    "        n_values = np.array([0] + n_values)\n",
    "        indices = np.cumsum(n_values)\n",
    "\n",
    "        column_indices = (X_int + indices[:-1]).ravel()[mask]\n",
    "        row_indices = np.repeat(np.arange(n_samples, dtype=np.int32),\n",
    "                                n_features)[mask]\n",
    "        data = np.ones(n_samples * n_features)[mask]\n",
    "\n",
    "        out = sparse.csc_matrix((data, (row_indices, column_indices)),\n",
    "                                shape=(n_samples, indices[-1]),\n",
    "                                dtype=self.dtype).tocsr()\n",
    "        if self.encoding == 'onehot-dense':\n",
    "            return out.toarray()\n",
    "        else:\n",
    "            return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fetchHousingData(housingURL = housing_URL, housingPath = housing_Path):\n",
    "    if not os.path.isdir(housingPath):\n",
    "        os.makedirs(housingPath)\n",
    "    tgzPath = os.path.join(housingPath, \"housing.tgz\")\n",
    "    urllib.request.urlretrieve(housingURL, tgzPath)\n",
    "    housingTGZ = tarfile.open(tgzPath)\n",
    "    housingTGZ.extractall(path=housingPath)\n",
    "    housingTGZ.close()\n",
    "\n",
    "def loadHousingData(housingPath = housing_Path):\n",
    "    csvPath = os.path.join(housingPath, \"housing.csv\")\n",
    "    return pd.read_csv(csvPath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20640 entries, 0 to 20639\n",
      "Data columns (total 10 columns):\n",
      "longitude             20640 non-null float64\n",
      "latitude              20640 non-null float64\n",
      "housing_median_age    20640 non-null float64\n",
      "total_rooms           20640 non-null float64\n",
      "total_bedrooms        20433 non-null float64\n",
      "population            20640 non-null float64\n",
      "households            20640 non-null float64\n",
      "median_income         20640 non-null float64\n",
      "median_house_value    20640 non-null float64\n",
      "ocean_proximity       20640 non-null object\n",
      "dtypes: float64(9), object(1)\n",
      "memory usage: 1.6+ MB\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20433.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-119.569704</td>\n",
       "      <td>35.631861</td>\n",
       "      <td>28.639486</td>\n",
       "      <td>2635.763081</td>\n",
       "      <td>537.870553</td>\n",
       "      <td>1425.476744</td>\n",
       "      <td>499.539680</td>\n",
       "      <td>3.870671</td>\n",
       "      <td>206855.816909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.003532</td>\n",
       "      <td>2.135952</td>\n",
       "      <td>12.585558</td>\n",
       "      <td>2181.615252</td>\n",
       "      <td>421.385070</td>\n",
       "      <td>1132.462122</td>\n",
       "      <td>382.329753</td>\n",
       "      <td>1.899822</td>\n",
       "      <td>115395.615874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-124.350000</td>\n",
       "      <td>32.540000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.499900</td>\n",
       "      <td>14999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-121.800000</td>\n",
       "      <td>33.930000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1447.750000</td>\n",
       "      <td>296.000000</td>\n",
       "      <td>787.000000</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>2.563400</td>\n",
       "      <td>119600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-118.490000</td>\n",
       "      <td>34.260000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>2127.000000</td>\n",
       "      <td>435.000000</td>\n",
       "      <td>1166.000000</td>\n",
       "      <td>409.000000</td>\n",
       "      <td>3.534800</td>\n",
       "      <td>179700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-118.010000</td>\n",
       "      <td>37.710000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>3148.000000</td>\n",
       "      <td>647.000000</td>\n",
       "      <td>1725.000000</td>\n",
       "      <td>605.000000</td>\n",
       "      <td>4.743250</td>\n",
       "      <td>264725.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>-114.310000</td>\n",
       "      <td>41.950000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>39320.000000</td>\n",
       "      <td>6445.000000</td>\n",
       "      <td>35682.000000</td>\n",
       "      <td>6082.000000</td>\n",
       "      <td>15.000100</td>\n",
       "      <td>500001.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
       "count  20640.000000  20640.000000        20640.000000  20640.000000   \n",
       "mean    -119.569704     35.631861           28.639486   2635.763081   \n",
       "std        2.003532      2.135952           12.585558   2181.615252   \n",
       "min     -124.350000     32.540000            1.000000      2.000000   \n",
       "25%     -121.800000     33.930000           18.000000   1447.750000   \n",
       "50%     -118.490000     34.260000           29.000000   2127.000000   \n",
       "75%     -118.010000     37.710000           37.000000   3148.000000   \n",
       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
       "\n",
       "       total_bedrooms    population    households  median_income  \\\n",
       "count    20433.000000  20640.000000  20640.000000   20640.000000   \n",
       "mean       537.870553   1425.476744    499.539680       3.870671   \n",
       "std        421.385070   1132.462122    382.329753       1.899822   \n",
       "min          1.000000      3.000000      1.000000       0.499900   \n",
       "25%        296.000000    787.000000    280.000000       2.563400   \n",
       "50%        435.000000   1166.000000    409.000000       3.534800   \n",
       "75%        647.000000   1725.000000    605.000000       4.743250   \n",
       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
       "\n",
       "       median_house_value  \n",
       "count        20640.000000  \n",
       "mean        206855.816909  \n",
       "std         115395.615874  \n",
       "min          14999.000000  \n",
       "25%         119600.000000  \n",
       "50%         179700.000000  \n",
       "75%         264725.000000  \n",
       "max         500001.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fetchHousingData()\n",
    "housing = loadHousingData()\n",
    "housing.head()\n",
    "housing.info()\n",
    "housing[\"ocean_proximity\"].value_counts()\n",
    "housing.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x237279b4390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "housing.hist(bins=50, figsize=(20,15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Split Randomly\n",
    "train_set, test_set = train_test_split(housing, test_size=0.2, random_state=42)\n",
    "\n",
    "#Split by Stratified Random Sample based on an attribute\n",
    "\n",
    "housing[\"income_cat\"] = np.ceil(housing[\"median_income\"]/1.5)\n",
    "housing[\"income_cat\"].where(housing['income_cat'] < 5, 5, inplace=True)\n",
    "\n",
    "split = StratifiedShuffleSplit(n_splits = 1, test_size=0.2, random_state=42)\n",
    "for train_index, test_index in split.split(housing, housing['income_cat']):\n",
    "    strat_train = housing.loc[train_index]\n",
    "    strat_test = housing.loc[test_index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2372c4ea518>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2372c4d1c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing = strat_train.copy()\n",
    "housing.plot(kind='scatter', x=\"longitude\", y='latitude', alpha = 0.4,\n",
    "            s=housing['population']/100, label='population', figsize=(10,7),\n",
    "            c=\"median_house_value\", cmap=plt.get_cmap(\"hsv\"), colorbar=True\n",
    "            )\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000002372BF34550>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372CCC4D68>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372C2BDD68>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372C2F2DD8>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002372C32EE48>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372C32EE80>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372C39D748>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372C3BD5C0>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002372CB626D8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372C3A8AC8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372BD80EB8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372A9D6128>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002372BD066A0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372BD4C438>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372BC8C978>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002372C5AC5C0>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2372bf560f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr_matrix = housing.corr()\n",
    "corr_matrix[\"median_house_value\"].sort_values(ascending=True)\n",
    "attributes = [\"median_house_value\", \"median_income\", \"total_rooms\", \"housing_median_age\"]\n",
    "scatter_matrix(housing[attributes], figsize=(12,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2372bc4eb38>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2372ccab860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind='scatter', x=\"median_income\", y=\"median_house_value\", alpha=0.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing[\"rooms_per_household\"] = housing[\"total_rooms\"]/housing[\"households\"]\n",
    "housing[\"bedrooms_per_room\"] = housing[\"total_bedrooms\"]/housing[\"total_rooms\"]\n",
    "housing[\"population_per_household\"] = housing[\"population\"]/housing[\"households\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "bedrooms_per_room          -0.259984\n",
       "latitude                   -0.142724\n",
       "longitude                  -0.047432\n",
       "population                 -0.026920\n",
       "population_per_household   -0.021985\n",
       "total_bedrooms              0.047689\n",
       "households                  0.064506\n",
       "housing_median_age          0.114110\n",
       "total_rooms                 0.135097\n",
       "rooms_per_household         0.146285\n",
       "income_cat                  0.642274\n",
       "median_income               0.687160\n",
       "median_house_value          1.000000\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix = housing.corr()\n",
    "corr_matrix[\"median_house_value\"].sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing = strat_train.drop(\"median_house_value\", axis =1)\n",
    "housing_labels = strat_train[\"median_house_value\"].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19480</th>\n",
       "      <td>-120.97</td>\n",
       "      <td>37.66</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2930.0</td>\n",
       "      <td>588.0</td>\n",
       "      <td>1448.0</td>\n",
       "      <td>570.0</td>\n",
       "      <td>3.5395</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8879</th>\n",
       "      <td>-118.50</td>\n",
       "      <td>34.04</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2233.0</td>\n",
       "      <td>317.0</td>\n",
       "      <td>769.0</td>\n",
       "      <td>277.0</td>\n",
       "      <td>8.3839</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13685</th>\n",
       "      <td>-117.24</td>\n",
       "      <td>34.15</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2041.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>6.0000</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4937</th>\n",
       "      <td>-118.26</td>\n",
       "      <td>33.99</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1865.0</td>\n",
       "      <td>465.0</td>\n",
       "      <td>1916.0</td>\n",
       "      <td>438.0</td>\n",
       "      <td>1.8242</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4861</th>\n",
       "      <td>-118.28</td>\n",
       "      <td>34.02</td>\n",
       "      <td>29.0</td>\n",
       "      <td>515.0</td>\n",
       "      <td>229.0</td>\n",
       "      <td>2690.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>0.4999</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16365</th>\n",
       "      <td>-121.31</td>\n",
       "      <td>38.02</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4157.0</td>\n",
       "      <td>951.0</td>\n",
       "      <td>2734.0</td>\n",
       "      <td>879.0</td>\n",
       "      <td>2.7981</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19684</th>\n",
       "      <td>-121.62</td>\n",
       "      <td>39.14</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2183.0</td>\n",
       "      <td>559.0</td>\n",
       "      <td>1202.0</td>\n",
       "      <td>506.0</td>\n",
       "      <td>1.6902</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19234</th>\n",
       "      <td>-122.69</td>\n",
       "      <td>38.51</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3364.0</td>\n",
       "      <td>501.0</td>\n",
       "      <td>1442.0</td>\n",
       "      <td>506.0</td>\n",
       "      <td>6.6854</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13956</th>\n",
       "      <td>-117.06</td>\n",
       "      <td>34.17</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2520.0</td>\n",
       "      <td>582.0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>2.7120</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2390</th>\n",
       "      <td>-119.46</td>\n",
       "      <td>36.91</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2980.0</td>\n",
       "      <td>495.0</td>\n",
       "      <td>1184.0</td>\n",
       "      <td>429.0</td>\n",
       "      <td>3.9141</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11176</th>\n",
       "      <td>-117.96</td>\n",
       "      <td>33.83</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2838.0</td>\n",
       "      <td>649.0</td>\n",
       "      <td>1758.0</td>\n",
       "      <td>593.0</td>\n",
       "      <td>3.3831</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15614</th>\n",
       "      <td>-122.41</td>\n",
       "      <td>37.81</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1178.0</td>\n",
       "      <td>545.0</td>\n",
       "      <td>592.0</td>\n",
       "      <td>441.0</td>\n",
       "      <td>3.6728</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2953</th>\n",
       "      <td>-119.02</td>\n",
       "      <td>35.35</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1239.0</td>\n",
       "      <td>251.0</td>\n",
       "      <td>776.0</td>\n",
       "      <td>272.0</td>\n",
       "      <td>1.9830</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13209</th>\n",
       "      <td>-117.72</td>\n",
       "      <td>34.05</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1841.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>1243.0</td>\n",
       "      <td>394.0</td>\n",
       "      <td>4.0614</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6569</th>\n",
       "      <td>-118.15</td>\n",
       "      <td>34.20</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1505.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>857.0</td>\n",
       "      <td>269.0</td>\n",
       "      <td>4.5000</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5825</th>\n",
       "      <td>-118.30</td>\n",
       "      <td>34.19</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3615.0</td>\n",
       "      <td>913.0</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>852.0</td>\n",
       "      <td>3.5083</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18086</th>\n",
       "      <td>-122.05</td>\n",
       "      <td>37.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>4111.0</td>\n",
       "      <td>538.0</td>\n",
       "      <td>1585.0</td>\n",
       "      <td>568.0</td>\n",
       "      <td>9.2298</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16718</th>\n",
       "      <td>-120.66</td>\n",
       "      <td>35.49</td>\n",
       "      <td>17.0</td>\n",
       "      <td>4422.0</td>\n",
       "      <td>945.0</td>\n",
       "      <td>2307.0</td>\n",
       "      <td>885.0</td>\n",
       "      <td>2.8285</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13600</th>\n",
       "      <td>-117.25</td>\n",
       "      <td>34.16</td>\n",
       "      <td>37.0</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>278.0</td>\n",
       "      <td>744.0</td>\n",
       "      <td>274.0</td>\n",
       "      <td>3.7188</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13989</th>\n",
       "      <td>-117.19</td>\n",
       "      <td>34.94</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2034.0</td>\n",
       "      <td>444.0</td>\n",
       "      <td>1097.0</td>\n",
       "      <td>367.0</td>\n",
       "      <td>2.1522</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15168</th>\n",
       "      <td>-117.06</td>\n",
       "      <td>33.02</td>\n",
       "      <td>24.0</td>\n",
       "      <td>830.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>279.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>1.9176</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6747</th>\n",
       "      <td>-118.07</td>\n",
       "      <td>34.11</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2869.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>533.0</td>\n",
       "      <td>5.0736</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7398</th>\n",
       "      <td>-118.24</td>\n",
       "      <td>33.96</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1338.0</td>\n",
       "      <td>366.0</td>\n",
       "      <td>1765.0</td>\n",
       "      <td>388.0</td>\n",
       "      <td>1.7778</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5562</th>\n",
       "      <td>-118.28</td>\n",
       "      <td>33.91</td>\n",
       "      <td>41.0</td>\n",
       "      <td>620.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2.6546</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16121</th>\n",
       "      <td>-122.46</td>\n",
       "      <td>37.79</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2059.0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>999.0</td>\n",
       "      <td>402.0</td>\n",
       "      <td>3.7419</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12380</th>\n",
       "      <td>-116.47</td>\n",
       "      <td>33.77</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4300.0</td>\n",
       "      <td>767.0</td>\n",
       "      <td>1557.0</td>\n",
       "      <td>669.0</td>\n",
       "      <td>4.4107</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5618</th>\n",
       "      <td>-118.23</td>\n",
       "      <td>33.78</td>\n",
       "      <td>20.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2.5588</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10060</th>\n",
       "      <td>-121.06</td>\n",
       "      <td>39.25</td>\n",
       "      <td>17.0</td>\n",
       "      <td>3127.0</td>\n",
       "      <td>539.0</td>\n",
       "      <td>1390.0</td>\n",
       "      <td>520.0</td>\n",
       "      <td>3.9537</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18067</th>\n",
       "      <td>-122.03</td>\n",
       "      <td>37.29</td>\n",
       "      <td>22.0</td>\n",
       "      <td>3118.0</td>\n",
       "      <td>438.0</td>\n",
       "      <td>1147.0</td>\n",
       "      <td>425.0</td>\n",
       "      <td>10.3653</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4471</th>\n",
       "      <td>-118.17</td>\n",
       "      <td>34.09</td>\n",
       "      <td>33.0</td>\n",
       "      <td>2907.0</td>\n",
       "      <td>797.0</td>\n",
       "      <td>3212.0</td>\n",
       "      <td>793.0</td>\n",
       "      <td>2.2348</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19786</th>\n",
       "      <td>-122.86</td>\n",
       "      <td>40.56</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1350.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>423.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>1.7393</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9969</th>\n",
       "      <td>-122.48</td>\n",
       "      <td>38.51</td>\n",
       "      <td>49.0</td>\n",
       "      <td>1977.0</td>\n",
       "      <td>393.0</td>\n",
       "      <td>741.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>3.1312</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14621</th>\n",
       "      <td>-117.17</td>\n",
       "      <td>32.78</td>\n",
       "      <td>17.0</td>\n",
       "      <td>3845.0</td>\n",
       "      <td>1051.0</td>\n",
       "      <td>3102.0</td>\n",
       "      <td>944.0</td>\n",
       "      <td>2.3658</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>579</th>\n",
       "      <td>-122.07</td>\n",
       "      <td>37.71</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1808.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>746.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>5.3015</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11682</th>\n",
       "      <td>-118.01</td>\n",
       "      <td>33.87</td>\n",
       "      <td>25.0</td>\n",
       "      <td>6348.0</td>\n",
       "      <td>1615.0</td>\n",
       "      <td>4188.0</td>\n",
       "      <td>1497.0</td>\n",
       "      <td>3.1390</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>-122.21</td>\n",
       "      <td>37.78</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1702.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>1227.0</td>\n",
       "      <td>407.0</td>\n",
       "      <td>1.7188</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12130</th>\n",
       "      <td>-117.23</td>\n",
       "      <td>33.94</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2405.0</td>\n",
       "      <td>537.0</td>\n",
       "      <td>1594.0</td>\n",
       "      <td>517.0</td>\n",
       "      <td>3.0789</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16441</th>\n",
       "      <td>-121.29</td>\n",
       "      <td>38.14</td>\n",
       "      <td>34.0</td>\n",
       "      <td>2770.0</td>\n",
       "      <td>544.0</td>\n",
       "      <td>1409.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>3.2338</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11016</th>\n",
       "      <td>-117.82</td>\n",
       "      <td>33.76</td>\n",
       "      <td>33.0</td>\n",
       "      <td>2774.0</td>\n",
       "      <td>428.0</td>\n",
       "      <td>1229.0</td>\n",
       "      <td>407.0</td>\n",
       "      <td>6.2944</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19934</th>\n",
       "      <td>-119.34</td>\n",
       "      <td>36.31</td>\n",
       "      <td>14.0</td>\n",
       "      <td>1635.0</td>\n",
       "      <td>422.0</td>\n",
       "      <td>870.0</td>\n",
       "      <td>399.0</td>\n",
       "      <td>2.7000</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1364</th>\n",
       "      <td>-122.14</td>\n",
       "      <td>38.03</td>\n",
       "      <td>42.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2.5795</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>-120.37</td>\n",
       "      <td>38.23</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4401.0</td>\n",
       "      <td>829.0</td>\n",
       "      <td>924.0</td>\n",
       "      <td>383.0</td>\n",
       "      <td>2.6942</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5364</th>\n",
       "      <td>-118.42</td>\n",
       "      <td>34.04</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1358.0</td>\n",
       "      <td>272.0</td>\n",
       "      <td>574.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>5.6454</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11703</th>\n",
       "      <td>-117.97</td>\n",
       "      <td>33.88</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>1172.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>6.0394</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10356</th>\n",
       "      <td>-117.67</td>\n",
       "      <td>33.60</td>\n",
       "      <td>25.0</td>\n",
       "      <td>3164.0</td>\n",
       "      <td>449.0</td>\n",
       "      <td>1517.0</td>\n",
       "      <td>453.0</td>\n",
       "      <td>6.7921</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15270</th>\n",
       "      <td>-117.29</td>\n",
       "      <td>33.08</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3225.0</td>\n",
       "      <td>515.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>5.7787</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3754</th>\n",
       "      <td>-118.37</td>\n",
       "      <td>34.18</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1608.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>1217.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>2.9728</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12166</th>\n",
       "      <td>-117.14</td>\n",
       "      <td>33.81</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4496.0</td>\n",
       "      <td>756.0</td>\n",
       "      <td>2044.0</td>\n",
       "      <td>695.0</td>\n",
       "      <td>3.2778</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6003</th>\n",
       "      <td>-117.77</td>\n",
       "      <td>34.08</td>\n",
       "      <td>27.0</td>\n",
       "      <td>5929.0</td>\n",
       "      <td>932.0</td>\n",
       "      <td>2817.0</td>\n",
       "      <td>828.0</td>\n",
       "      <td>6.0434</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7364</th>\n",
       "      <td>-118.20</td>\n",
       "      <td>33.97</td>\n",
       "      <td>43.0</td>\n",
       "      <td>825.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>820.0</td>\n",
       "      <td>184.0</td>\n",
       "      <td>1.8897</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6563</th>\n",
       "      <td>-118.13</td>\n",
       "      <td>34.20</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1271.0</td>\n",
       "      <td>236.0</td>\n",
       "      <td>573.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>4.9312</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12053</th>\n",
       "      <td>-117.56</td>\n",
       "      <td>33.88</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1196.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>1052.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>2.0682</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13908</th>\n",
       "      <td>-116.40</td>\n",
       "      <td>34.09</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4855.0</td>\n",
       "      <td>872.0</td>\n",
       "      <td>2098.0</td>\n",
       "      <td>765.0</td>\n",
       "      <td>3.2723</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11159</th>\n",
       "      <td>-118.01</td>\n",
       "      <td>33.82</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1960.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>1356.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>4.0625</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15775</th>\n",
       "      <td>-122.45</td>\n",
       "      <td>37.77</td>\n",
       "      <td>52.0</td>\n",
       "      <td>3095.0</td>\n",
       "      <td>682.0</td>\n",
       "      <td>1269.0</td>\n",
       "      <td>639.0</td>\n",
       "      <td>3.5750</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16354 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "19480    -120.97     37.66                24.0       2930.0           588.0   \n",
       "8879     -118.50     34.04                52.0       2233.0           317.0   \n",
       "13685    -117.24     34.15                26.0       2041.0           293.0   \n",
       "4937     -118.26     33.99                47.0       1865.0           465.0   \n",
       "4861     -118.28     34.02                29.0        515.0           229.0   \n",
       "16365    -121.31     38.02                24.0       4157.0           951.0   \n",
       "19684    -121.62     39.14                41.0       2183.0           559.0   \n",
       "19234    -122.69     38.51                18.0       3364.0           501.0   \n",
       "13956    -117.06     34.17                21.0       2520.0           582.0   \n",
       "2390     -119.46     36.91                12.0       2980.0           495.0   \n",
       "11176    -117.96     33.83                30.0       2838.0           649.0   \n",
       "15614    -122.41     37.81                25.0       1178.0           545.0   \n",
       "2953     -119.02     35.35                42.0       1239.0           251.0   \n",
       "13209    -117.72     34.05                 8.0       1841.0           409.0   \n",
       "6569     -118.15     34.20                46.0       1505.0           261.0   \n",
       "5825     -118.30     34.19                14.0       3615.0           913.0   \n",
       "18086    -122.05     37.31                25.0       4111.0           538.0   \n",
       "16718    -120.66     35.49                17.0       4422.0           945.0   \n",
       "13600    -117.25     34.16                37.0       1709.0           278.0   \n",
       "13989    -117.19     34.94                31.0       2034.0           444.0   \n",
       "15168    -117.06     33.02                24.0        830.0           190.0   \n",
       "6747     -118.07     34.11                41.0       2869.0           563.0   \n",
       "7398     -118.24     33.96                44.0       1338.0           366.0   \n",
       "5562     -118.28     33.91                41.0        620.0           133.0   \n",
       "16121    -122.46     37.79                52.0       2059.0           416.0   \n",
       "...          ...       ...                 ...          ...             ...   \n",
       "12380    -116.47     33.77                26.0       4300.0           767.0   \n",
       "5618     -118.23     33.78                20.0         59.0            24.0   \n",
       "10060    -121.06     39.25                17.0       3127.0           539.0   \n",
       "18067    -122.03     37.29                22.0       3118.0           438.0   \n",
       "4471     -118.17     34.09                33.0       2907.0           797.0   \n",
       "19786    -122.86     40.56                12.0       1350.0           300.0   \n",
       "9969     -122.48     38.51                49.0       1977.0           393.0   \n",
       "14621    -117.17     32.78                17.0       3845.0          1051.0   \n",
       "579      -122.07     37.71                40.0       1808.0           302.0   \n",
       "11682    -118.01     33.87                25.0       6348.0          1615.0   \n",
       "245      -122.21     37.78                43.0       1702.0           460.0   \n",
       "12130    -117.23     33.94                 8.0       2405.0           537.0   \n",
       "16441    -121.29     38.14                34.0       2770.0           544.0   \n",
       "11016    -117.82     33.76                33.0       2774.0           428.0   \n",
       "19934    -119.34     36.31                14.0       1635.0           422.0   \n",
       "1364     -122.14     38.03                42.0        118.0            34.0   \n",
       "1236     -120.37     38.23                13.0       4401.0           829.0   \n",
       "5364     -118.42     34.04                52.0       1358.0           272.0   \n",
       "11703    -117.97     33.88                16.0       2003.0           300.0   \n",
       "10356    -117.67     33.60                25.0       3164.0           449.0   \n",
       "15270    -117.29     33.08                18.0       3225.0           515.0   \n",
       "3754     -118.37     34.18                36.0       1608.0           373.0   \n",
       "12166    -117.14     33.81                13.0       4496.0           756.0   \n",
       "6003     -117.77     34.08                27.0       5929.0           932.0   \n",
       "7364     -118.20     33.97                43.0        825.0           212.0   \n",
       "6563     -118.13     34.20                46.0       1271.0           236.0   \n",
       "12053    -117.56     33.88                40.0       1196.0           294.0   \n",
       "13908    -116.40     34.09                 9.0       4855.0           872.0   \n",
       "11159    -118.01     33.82                31.0       1960.0           380.0   \n",
       "15775    -122.45     37.77                52.0       3095.0           682.0   \n",
       "\n",
       "       population  households  median_income ocean_proximity  income_cat  \n",
       "17606       710.0       339.0         2.7042       <1H OCEAN         2.0  \n",
       "18632       306.0       113.0         6.4214       <1H OCEAN         5.0  \n",
       "14650       936.0       462.0         2.8621      NEAR OCEAN         2.0  \n",
       "3230       1460.0       353.0         1.8839          INLAND         2.0  \n",
       "3555       4459.0      1463.0         3.0347       <1H OCEAN         3.0  \n",
       "19480      1448.0       570.0         3.5395          INLAND         3.0  \n",
       "8879        769.0       277.0         8.3839       <1H OCEAN         5.0  \n",
       "13685       936.0       375.0         6.0000          INLAND         4.0  \n",
       "4937       1916.0       438.0         1.8242       <1H OCEAN         2.0  \n",
       "4861       2690.0       217.0         0.4999       <1H OCEAN         1.0  \n",
       "16365      2734.0       879.0         2.7981          INLAND         2.0  \n",
       "19684      1202.0       506.0         1.6902          INLAND         2.0  \n",
       "19234      1442.0       506.0         6.6854       <1H OCEAN         5.0  \n",
       "13956       416.0       151.0         2.7120          INLAND         2.0  \n",
       "2390       1184.0       429.0         3.9141          INLAND         3.0  \n",
       "11176      1758.0       593.0         3.3831       <1H OCEAN         3.0  \n",
       "15614       592.0       441.0         3.6728        NEAR BAY         3.0  \n",
       "2953        776.0       272.0         1.9830          INLAND         2.0  \n",
       "13209      1243.0       394.0         4.0614          INLAND         3.0  \n",
       "6569        857.0       269.0         4.5000          INLAND         3.0  \n",
       "5825       1924.0       852.0         3.5083       <1H OCEAN         3.0  \n",
       "18086      1585.0       568.0         9.2298       <1H OCEAN         5.0  \n",
       "16718      2307.0       885.0         2.8285       <1H OCEAN         2.0  \n",
       "13600       744.0       274.0         3.7188          INLAND         3.0  \n",
       "13989      1097.0       367.0         2.1522          INLAND         2.0  \n",
       "15168       279.0       196.0         1.9176       <1H OCEAN         2.0  \n",
       "6747       1627.0       533.0         5.0736       <1H OCEAN         4.0  \n",
       "7398       1765.0       388.0         1.7778       <1H OCEAN         2.0  \n",
       "5562        642.0       162.0         2.6546       <1H OCEAN         2.0  \n",
       "16121       999.0       402.0         3.7419        NEAR BAY         3.0  \n",
       "...           ...         ...            ...             ...         ...  \n",
       "12380      1557.0       669.0         4.4107          INLAND         3.0  \n",
       "5618         69.0        23.0         2.5588      NEAR OCEAN         2.0  \n",
       "10060      1390.0       520.0         3.9537          INLAND         3.0  \n",
       "18067      1147.0       425.0        10.3653       <1H OCEAN         5.0  \n",
       "4471       3212.0       793.0         2.2348       <1H OCEAN         2.0  \n",
       "19786       423.0       172.0         1.7393          INLAND         2.0  \n",
       "9969        741.0       339.0         3.1312          INLAND         3.0  \n",
       "14621      3102.0       944.0         2.3658      NEAR OCEAN         2.0  \n",
       "579         746.0       270.0         5.3015        NEAR BAY         4.0  \n",
       "11682      4188.0      1497.0         3.1390       <1H OCEAN         3.0  \n",
       "245        1227.0       407.0         1.7188        NEAR BAY         2.0  \n",
       "12130      1594.0       517.0         3.0789          INLAND         3.0  \n",
       "16441      1409.0       535.0         3.2338          INLAND         3.0  \n",
       "11016      1229.0       407.0         6.2944       <1H OCEAN         5.0  \n",
       "19934       870.0       399.0         2.7000          INLAND         2.0  \n",
       "1364         54.0        30.0         2.5795        NEAR BAY         2.0  \n",
       "1236        924.0       383.0         2.6942          INLAND         2.0  \n",
       "5364        574.0       267.0         5.6454       <1H OCEAN         4.0  \n",
       "11703      1172.0       318.0         6.0394       <1H OCEAN         5.0  \n",
       "10356      1517.0       453.0         6.7921       <1H OCEAN         5.0  \n",
       "15270      1463.0       476.0         5.7787      NEAR OCEAN         4.0  \n",
       "3754       1217.0       374.0         2.9728       <1H OCEAN         2.0  \n",
       "12166      2044.0       695.0         3.2778          INLAND         3.0  \n",
       "6003       2817.0       828.0         6.0434          INLAND         5.0  \n",
       "7364        820.0       184.0         1.8897       <1H OCEAN         2.0  \n",
       "6563        573.0       210.0         4.9312          INLAND         4.0  \n",
       "12053      1052.0       258.0         2.0682          INLAND         2.0  \n",
       "13908      2098.0       765.0         3.2723          INLAND         3.0  \n",
       "11159      1356.0       356.0         4.0625       <1H OCEAN         3.0  \n",
       "15775      1269.0       639.0         3.5750        NEAR BAY         3.0  \n",
       "\n",
       "[16354 rows x 10 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.dropna(subset=[\"total_bedrooms\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "imputer = Imputer(strategy=\"median\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Imputer(axis=0, copy=True, missing_values='NaN', strategy='median', verbose=0)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_num = housing.drop(\"ocean_proximity\", axis = 1)\n",
    "imputer.fit(housing_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-118.51  ,   34.26  ,   29.    , 2119.5   ,  433.    , 1164.    ,\n",
       "        408.    ,    3.5409,    3.    ])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imputer.statistics_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-118.51  ,   34.26  ,   29.    , 2119.5   ,  433.    , 1164.    ,\n",
       "        408.    ,    3.5409,    3.    ])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_num.median().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_cat = housing[\"ocean_proximity\"]\n",
    "housing_cat_encoded, housing_categories = housing_cat.factorize()\n",
    "#^ML Algorithms might treat two values in this category similarly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<16512x5 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 16512 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "encoder = OneHotEncoder() \n",
    "housing_cat_1hot = encoder.fit_transform(housing_cat_encoded.reshape(-1,1))\n",
    "housing_cat_1hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<16512x5 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 16512 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_encoder = CategoricalEncoder()\n",
    "housing_cat_reshaped = housing_cat.values.reshape(-1,1)\n",
    "housing_cat_1hot = cat_encoder.fit_transform(housing_cat_reshaped)\n",
    "housing_cat_1hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
       "       dtype=object)]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_encoder.categories_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.base import BaseEstimator, TransformerMixin\n",
    "rooms_ix, bedrooms_ix, population_ix, household_ix = 3,4,5,6\n",
    "\n",
    "class CombinedAttributesAdder(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, add_bedrooms_per_room = True): # no *args or **kargs\n",
    "        self.add_bedrooms_per_room = add_bedrooms_per_room\n",
    "    def fit(self, X, y=None):\n",
    "        return self  # nothing else to do\n",
    "    def transform(self, X, y=None):\n",
    "        rooms_per_household = X[:, rooms_ix] / X[:, household_ix]\n",
    "        population_per_household = X[:, population_ix] / X[:, household_ix]\n",
    "        if self.add_bedrooms_per_room:\n",
    "            bedrooms_per_room = X[:, bedrooms_ix] / X[:, rooms_ix]\n",
    "            return np.c_[X, rooms_per_household, population_per_household,\n",
    "                         bedrooms_per_room]\n",
    "        else:\n",
    "            return np.c_[X, rooms_per_household, population_per_household]\n",
    "\n",
    "attr_adder = CombinedAttributesAdder(add_bedrooms_per_room=False)\n",
    "housing_extra_attribs = attr_adder.transform(housing.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "num_pipeline = Pipeline([\n",
    "        ('imputer', Imputer(strategy=\"median\")),\n",
    "        ('attribs_adder', CombinedAttributesAdder()),\n",
    "        ('std_scaler', StandardScaler()),\n",
    "    ])\n",
    "\n",
    "housing_num_tr = num_pipeline.fit_transform(housing_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.15604281,  0.77194962,  0.74333089, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [-1.17602483,  0.6596948 , -1.1653172 , ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [ 1.18684903, -1.34218285,  0.18664186, ...,  0.        ,\n",
       "         0.        ,  1.        ],\n",
       "       ...,\n",
       "       [ 1.58648943, -0.72478134, -1.56295222, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [ 0.78221312, -0.85106801,  0.18664186, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [-1.43579109,  0.99645926,  1.85670895, ...,  0.        ,\n",
       "         1.        ,  0.        ]])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.base import BaseEstimator, TransformerMixin\n",
    "\n",
    "# Create a class to select numerical or categorical columns \n",
    "# since Scikit-Learn doesn't handle DataFrames yet\n",
    "class DataFrameSelector(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, attribute_names):\n",
    "        self.attribute_names = attribute_names\n",
    "    def fit(self, X, y=None):\n",
    "        return self\n",
    "    def transform(self, X):\n",
    "        return X[self.attribute_names].values\n",
    "    \n",
    "num_attribs = list(housing_num)\n",
    "cat_attribs = [\"ocean_proximity\"]\n",
    "\n",
    "num_pipeline = Pipeline([\n",
    "        ('selector', DataFrameSelector(num_attribs)),\n",
    "        ('imputer', Imputer(strategy=\"median\")),\n",
    "        ('attribs_adder', CombinedAttributesAdder()),\n",
    "        ('std_scaler', StandardScaler()),\n",
    "    ])\n",
    "\n",
    "cat_pipeline = Pipeline([\n",
    "        ('selector', DataFrameSelector(cat_attribs)),\n",
    "        ('cat_encoder', CategoricalEncoder(encoding=\"onehot-dense\")),\n",
    "    ])\n",
    "\n",
    "from sklearn.pipeline import FeatureUnion\n",
    "\n",
    "full_pipeline = FeatureUnion(transformer_list=[\n",
    "        (\"num_pipeline\", num_pipeline),\n",
    "        (\"cat_pipeline\", cat_pipeline),\n",
    "    ])\n",
    "\n",
    "housing_prepared = full_pipeline.fit_transform(housing)\n",
    "housing_prepared"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(16512, 17)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_prepared.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "lin_reg = LinearRegression()\n",
    "lin_reg.fit(housing_prepared, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions: [203682.37379543 326371.39370781 204218.64588245  58685.4770482\n",
      " 194213.06443039]\n"
     ]
    }
   ],
   "source": [
    "# let's try the full pipeline on a few training instances\n",
    "some_data = housing.iloc[:5]\n",
    "some_labels = housing_labels.iloc[:5]\n",
    "some_data_prepared = full_pipeline.transform(some_data)\n",
    "\n",
    "print(\"Predictions:\", lin_reg.predict(some_data_prepared))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Labels: [286600.0, 340600.0, 196900.0, 46300.0, 254500.0]\n"
     ]
    }
   ],
   "source": [
    "print(\"Labels:\", list(some_labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68376.64295459939"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "housing_predictions = lin_reg.predict(housing_prepared)\n",
    "lin_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "lin_rmse = np.sqrt(lin_mse)\n",
    "lin_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "\n",
    "tree_reg = DecisionTreeRegressor(random_state=42)\n",
    "tree_reg.fit(housing_prepared, housing_labels)\n",
    "housing_predictions = tree_reg.predict(housing_prepared)\n",
    "tree_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "tree_rmse = np.sqrt(tree_mse)\n",
    "tree_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores: [70307.54079165 67270.94561829 71361.89886493 68889.91784739\n",
      " 70992.94150631 74140.66907294 70607.72083897 70576.13836762\n",
      " 76433.16342183 70270.96266671]\n",
      "Mean: 71085.189899664\n",
      "Standard deviation: 2431.961029690467\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "scores = cross_val_score(tree_reg, housing_prepared, housing_labels,\n",
    "                         scoring=\"neg_mean_squared_error\", cv=10)\n",
    "tree_rmse_scores = np.sqrt(-scores)\n",
    "\n",
    "\n",
    "def display_scores(scores):\n",
    "    print(\"Scores:\", scores)\n",
    "    print(\"Mean:\", scores.mean())\n",
    "    print(\"Standard deviation:\", scores.std())\n",
    "\n",
    "display_scores(tree_rmse_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores: [66877.52325028 66608.120256   70575.91118868 74179.94799352\n",
      " 67683.32205678 71103.16843468 64782.65896552 67711.29940352\n",
      " 71080.40484136 67687.6384546 ]\n",
      "Mean: 68828.9994844933\n",
      "Standard deviation: 2662.761570610344\n"
     ]
    }
   ],
   "source": [
    "lin_scores = cross_val_score(lin_reg, housing_prepared, housing_labels,\n",
    "                             scoring=\"neg_mean_squared_error\", cv=10)\n",
    "lin_rmse_scores = np.sqrt(-lin_scores)\n",
    "display_scores(lin_rmse_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22112.540875989125"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "forest_reg = RandomForestRegressor(random_state=42)\n",
    "forest_reg.fit(housing_prepared, housing_labels)\n",
    "\n",
    "housing_predictions = forest_reg.predict(housing_prepared)\n",
    "forest_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "forest_rmse = np.sqrt(forest_mse)\n",
    "forest_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores: [51513.5500248  48821.99364978 53451.63889205 54910.55855153\n",
      " 50405.68166817 56772.90691171 51909.21824137 50516.14893695\n",
      " 55699.80788403 53107.7805515 ]\n",
      "Mean: 52710.92853118938\n",
      "Standard deviation: 2414.7271791176026\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "forest_scores = cross_val_score(forest_reg, housing_prepared, housing_labels,\n",
    "                                scoring=\"neg_mean_squared_error\", cv=10)\n",
    "forest_rmse_scores = np.sqrt(-forest_scores)\n",
    "display_scores(forest_rmse_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count       10.000000\n",
       "mean     68828.999484\n",
       "std       2806.797143\n",
       "min      64782.658966\n",
       "25%      67078.972952\n",
       "50%      67699.468929\n",
       "75%      70954.281428\n",
       "max      74179.947994\n",
       "dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "scores = cross_val_score(lin_reg, housing_prepared, housing_labels, scoring=\"neg_mean_squared_error\", cv=10)\n",
    "pd.Series(np.sqrt(-scores)).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'svr_rsme_scores' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-46-c44bce474f64>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[0msvr_scores\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msvm_reg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhousing_prepared\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhousing_labels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mscoring\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"neg_mean_squared_error\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[0msvr_rmse_scores\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msqrt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0msvr_scores\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 12\u001b[1;33m \u001b[0mdisplay_scores\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msvr_rsme_scores\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'svr_rsme_scores' is not defined"
     ]
    }
   ],
   "source": [
    "\n",
    "from sklearn.svm import SVR\n",
    "\n",
    "svm_reg = SVR(kernel=\"linear\")\n",
    "svm_reg.fit(housing_prepared, housing_labels)\n",
    "housing_predictions = svm_reg.predict(housing_prepared)\n",
    "svm_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "svm_rmse = np.sqrt(svm_mse)\n",
    "svm_rmse\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores: [101753.54978461 108380.51380685 106200.32161595 109301.66402916\n",
      " 106682.29073341 111849.88610827 106534.44353941 110576.7797446\n",
      " 109867.22584371 107754.78897031]\n",
      "Mean: 107890.14641762718\n",
      "Standard deviation: 2699.402075191871\n"
     ]
    }
   ],
   "source": [
    "svr_scores = cross_val_score(svm_reg, housing_prepared, housing_labels, scoring=\"neg_mean_squared_error\", cv=10)\n",
    "svr_rmse_scores = np.sqrt(-svr_scores)\n",
    "display_scores(svr_rmse_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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